@inproceedings{becc6a937ad9435d8e920ff8829d9b1f,
title = "Discovering web document associations for web site summarization",
abstract = "Complex web information structures prevent search engines from providing satisfactory context-sensitive retrieval. We see that in order to overcome this obstacle, it is essential to use techniques that re- cover the web authors' intentions and superimpose them with the users' retrieval contexts in summarizing web sites. Therefore, in this paper, we present a framework for discovering implicit associations among web documents for effective web site summarization. In the proposed frame- work, associations of web documents are induced by the web structure embedding them, as well as the contents of the documents and users' interests. We analyze the semantics of document associations and describe an algorithm which capture these semantics for enumerating and ranking possible document associations. We then use these asociations in creating context-sensitive summaries of web neighborhoods.",
author = "Kasim Candan and Li, {Wen Syan}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.; 3rd International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2001 ; Conference date: 05-09-2001 Through 07-09-2001",
year = "2001",
doi = "10.1007/3-540-44801-2_16",
language = "English (US)",
isbn = "3540425535",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "152--161",
editor = "Werner Winiwarter and Yahiko Kambayashi and Masatoshi Arikawa",
booktitle = "Data Warehousing and Knowledge Discovery - 3rd International Conference, DaWaK 2001, Proceedings",
}